AI delivers impact in CRE with the right data, culture, and leadership

Can CRE thrive amid digital transformation?

At the 2025 Altus Innovation Summit in London, Jorge Blanco, Chief Strategy Officer at Altus Group, opened up a panel discussion with a simple, but undeniable observation: “There is no question that these are very interesting times.” While commercial real estate (CRE) has been forced to navigate turbulent fiscal and monetary policies, persist through the socio-economic aftershocks of the pandemic, and adapt to a rapidly evolving risk landscape, technology offers new sources of competitive advantage. That is, if the industry is willing to embrace the right cultural and operational changes and accept that this significant technological disruption is here to stay.

By now, AI has become central to CRE dialogue, and the technology’s promise is clear: faster insights, better decision-making, and new revenue opportunities. However, without deliberate changes to incentives, data practices and operating models, AI will underdeliver. In other words, realizing the full value of AI requires the industry to fundamentally reshape its culture and operations, especially as it pertains to how data is created, shared, and governed. With this in mind, Blanco sat down with Katie Smith (Global Head of Performance, LaSalle Investment Management), Emilio Portes Cruz (Global Head of Innovation & Capital Markets, JLL), and Shubhra Srivastava (VP, Product Management, Altus Group) to zero in on the non‑technical barriers that will determine whether AI is a disruptive force for good or an expensive experiment.

Unlocking AI’s promise: Why data and culture matter

CRE may be late to many tech waves, but modern AI’s accessibility and ubiquity create an exciting inflection point. “I feel like we could almost jump ahead of the curve if we utilize AI in the right way,” Smith noted, alluding to the fact that organizations that move deliberately - prioritizing use cases with clear business impact - are likely to outpace peers who treat AI as a novelty.

However, this opportunity won’t be realized by models alone. Firms must pair AI with cleaner, better‑governed data, aligned incentives and operating models that enable cross‑team sharing, a willingness to experiment and human validation. As Portes Cruz explained, organizations need to “map out what is valuable that you’re generating” so investments prioritize high‑impact assets rather than endless data cleanup. Put simply, the technical elevator exists, but CRE must build the cultural and operational stairs to reach it. “When we just push technologies down and they don’t relate to what our teams are actually doing, they avoid them,” he added.

To advance, CRE leaders must focus on change management by investing not only in technology, but in the people and processes that power adoption. Upskilling teams, driving buy-in across business units with a cultural acceptance to fail fast and learn from these experiments, and communicating the tangible wins from AI and data projects will be just as essential as system upgrades.

Effective adoption requires alignment

The implementation of AI has seemingly ignited a great deal of doom spiralling, contributing to a landscape where cultural inertia - more than technical complexity - is the true bottleneck to AI innovation. But for CRE, AI remains poised as a valuable force multiplier for the people who understand markets and assets best - not a wholesale replacement of human expertise. If used properly, AI can offload repetitive tasks and surface insights faster. As Srivastava put it, the aim is to “use AI to do grunt work… while using human validation to ensure quality and accuracy” so professionals can focus on applying better judgment, enriching client relationships and tackling complex decisions that machines cannot replicate. “You always need human opinion in the process,” Smith added. “Real estate is different. Every building is unique, and behavioural economics – human judgment - still drives the industry.”

Portes Cruz added that the use of AI technology is already pervasive across the industry, and underscored the importance of deliberate governance, clear data ownership, and pilots focused on high‑value workflows that demonstrably move the top line. At the same time, ethical considerations must not be overlooked as AI adoption grows and, moving forward, organizations will need to ensure responsible practices are embedded in every data-driven initiative.

Cleaning, connecting, and governing data

Data serves as both the fuel and choke point for AI adoption and, with this in mind, firms must treat it as a governed asset rather than an afterthought. “Data is where all advanced analytics projects go to die,” Blanco quoted, crystallizing a frustration frequently echoed across the industry. Smith echoed this sentiment, noting that teams are “spending a huge amount of time cleaning data,” a drain that leadership must eliminate by instituting clear ownership, quality metrics and pragmatic prioritization of high‑value fields.

CRE leaders can cut through fragmentation by identifying a core set of high-value data assets, then invest in keeping them clean, up-to-date, and broadly accessible. “Not reinventing the wheel is big,” Srivastava commented. “If we have solved it in one part of the organization, let’s make sure it's getting used elsewhere.”

Data governance must also be systematized, not left to goodwill or heroics. As emphasized by Portes Cruz, metrics like coverage, timeliness, and accuracy should be transparently tied to team and personal performance. “It’s about mapping out what's valuable in your data set,” he explained. “Spend time identifying those and how you’re going to use them to anchor your services in those insights.”

However, even as organizations embrace new possibilities, operational headaches persist. “The state of data is what keeps me up at night,” Srivastava admitted. “Fragmentation, the lag from M&A and divestitures data integrations, the love of spreadsheets... but I’m optimistic.” By prioritizing integration, streamlining data practices, and encouraging a culture of sharing, CRE leaders are gradually transforming data from a stubborn barrier into a true source of value. Progress may be incremental, but the momentum is clearly building.

Creating a future-ready CRE industry

Where could these changes lead? “I really hope that in five years, we have changed,” Smith reflected. “We’re receiving more and more requests from clients for detailed data. It’s no longer enough to simply report a strong IRR - clients now want to understand the underlying drivers and see comparisons to peer benchmarks. Soon, proficiency in data-driven insights will be a baseline expectation across the industry.” This means organizations must develop data literacy and analytical capabilities across all roles, not just data scientists and technologists. Future CRE teams will need to interpret and act on data-driven insights as a core skill set.

Portes Cruz also painted a vision of an industry transformed not by outside disruption, but by CRE’s own embrace of these principles. “We haven’t seen a total disruption from an outside player yet, but it can happen. The industry is changing. We need to adapt these models to real estate and apply them to our problems.”

Srivastava’s vision centres on the widespread embrace of ‘invisible AI’, where point solutions fade into the background and professionals simply work smarter. “More connected, more personal, definitely more pervasive, even to the point where we don’t always realize it’s AI, but it’s just happening.”

Collaboration and leadership will define CRE’s next chapter

Ultimately, the road ahead requires not just new tools, but also new mindsets and capabilities. By prioritizing data governance, embracing collaboration, and equipping their people for a more analytical, tech-forward future, CRE leaders can ensure that innovation is both responsible and impactful, turning today’s challenges into tomorrow’s competitive advantages.

“If we do it thoughtfully and collaborate as an industry, we will end up better as we go through this,” Blanco concluded.